Which of several alternative population forecasts is the “best” or the most plausible? In published work summarized here, we use Taylor’s law (TL) and its quadratic generalization to select the best among six alternative projections (by Statistics Norway) of Norwegian county population density. We consider two time scales: long term (1978–2010 as the historical basis for projections of 2011–2040) and short term (2006–2010 as the historical basis for projections of 2011–2015). We find that the short-term projections selected as “best” by TL are more closely aligned than the four other projections with the recent county density data, and reflect the current high rate of international net immigration to Norway. Our approach needs to be further tested using other data and demographic forecasts.

This discussion piece is an extended review of the work on projecting the world’s population and human capital by country conducted by the Wittgenstein Centre (WIC). The project was led by Wolfgang Lutz, and its outcomes were published by Oxford University Press in a book that appeared in 2014. Using statistics from the book and elsewhere, this article starts with an overview of the development of educational attainment. The role that education plays in the WIC2014 model is identified. Definitions of ‘multi-dimensional’, ‘multi-state’, and ‘micro-simulation’ are offered, and are used to characterise the model. A thumbnail sketch of the main methods used in the projections is given. The final section sets out a possible agenda for the future development of the WIC2014 model. This review is intended to help readers tackle the more than 1,000 pages of argument and analysis in the book, which represents a major contribution to demographic research in the 21st century.

Research articles

Multistate Projections of Australia’s Indigenous Population: Interacting Area Group and Identification Status Change

James Raymer (corresponding author), School of Demography, Research School of Social Sciences, Australian National University, 9 Fellows Road, Acton ACT 2601, Australia Email: james.raymer@anu.edu.au Yanlin Shi, Department of Actuarial Studies and Business Analytics, Macquarie University, Australia James O’Donnell, School of Demography, Research School of Social Sciences, Australian National University, Australia Nicholas Biddle, Centre for Aboriginal Economic Policy Research and ANU Centre for Social Research and Methods, Research School of Social Sciences, Australian National University, Australia

In this paper, we develop a multistate projection model that allows the Australian Aboriginal and Torres Strait Islander (Indigenous) population to move between area classifications and Indigenous self-identification statuses. We combine data from the Australian Census Longitudinal Dataset and the 2011 census to estimate the transitions between 2006 and 2011. This information is then included in a multistate population projection model to illustrate the effects of migration and identification change over time in relation to natural increase (i.e., births – deaths). The results show how patterns of identification change differ by both age and type of migration, and how migration and identification change affect patterns of Indigenous population change across major cities, regional areas, and remote areas in Australia.

Will the population of today’s high-income countries continue to age throughout the remainder of the century? We answer this question by combining two methodologies, Bayesian hierarchical probabilistic population forecasting and the use of prospective ages, which are chronological ages adjusted for changes in life expectancy. We distinguish two variants of measures of aging: those that depend on fixed chronological ages and those that use prospective ages. Conventional measures do not, for example, distinguish between 65-year-olds in 2000 and 65- year-olds in 2100. In making forecasts of population aging over long periods of time, ignoring changes in the characteristics of people can lead to misleading results. It is preferable to use measures based on prospective ages in which expected changes in life expectancy are taken into account. We present probabilistic forecasts of population aging that use conventional and prospective measures for high-income countries as a group. The probabilistic forecasts based on conventional measures of aging show that the probability that aging will continue throughout the century is essentially one. In contrast, the probabilistic forecasts based on prospective measures of population aging show that population aging will almost certainly come to end well before the end of the century. Using prospective measures of population aging, we show that aging in high-income countries is likely a transitory phenomenon.

The public pension system in Italy is a defined contribution scheme based on the principle of actuarial fairness. The pension annuity is calculated starting from capitalised value and the Legislated Conversion Factors (LCFs) for each retirement age. The demographic parameters used by legislators in computing the LCFs are the survival probabilities of an average Italian, irrespective of gender or any characteristic except age. The aim of this paper is to analyse the impact of the differences in survival between men and women, and between individuals with different educational levels, on the calculation of the pension annuity, starting from the specific Conversion Factors (CFs). The gap between the LCFs and the factors obtained by allowing for differential survival across gender and socio-demographic groups (CFs) gives us a means of making a quantitative assessment of the implicit redistributive impacts of the annuity redistribution from individuals with a lower life expectancy to individuals with a higher life expectancy.

The adult lives of women and men are shaped by a wide range of choices and events pertaining to different life domains. In the literature, however, pregnancy intentions are typically studied in isolation from other life course intentions. We investigate the correspondence of birth intentions and outcomes in a life course cross-domain perspective that includes partnership, education, work, and housing. Using longitudinal data from the Generations and Gender Surveys, we examine the matching processes of individuals’ birth intentions with subsequent outcomes in Austria, Bulgaria, France, Hungary, and Lithuania. The results show that the intention to change residence is directly correlated with having a child among men and women living in a union, and that the intention to enter a partnership is correlated with childbearing among single men, but not among single women. Furthermore, we find that the intention to change jobs is inversely correlated with an intended childbirth, while it is directly correlated with an unintended childbirth. These findings suggest that the transition paths from birth intentions to birth outcomes should encompass a multi-dimensional life course perspective.

International migration is difficult to predict because of uncertainties. The identification of sources of uncertainty and the measurement and modelling of uncertainties are necessary, but they are not sufficient. Uncertainties should be reduced by accounting for the heterogeneity of migrants, the reasons why some people leave their country while most stay, and the causal mechanisms that lead to those choices. International migration takes place within a context of globalisation, technological change, growing interest in migration governance, and the emergence of a migration industry. Young people are more likely than older people to respond to these contextual factors, as they are better informed, have greater self-efficacy, and are more likely to have a social network abroad than previous generations. My aim in this paper is to present ideas for the causal forecasting of migration. Wolfgang Lutz’s demographic theory of socioeconomic change is a good point of departure. The cohort-replacement mechanism, which is central to Lutz’s theory, is extended to account for cohort heterogeneity, life-cycle transitions, and learning. I close the paper by concluding that the time has come to explore the causal mechanisms underlying migration, and to make optimal use of that knowledge to improve migration forecasts.

Muslim countries have experienced unprecedented demographic and social transitions in recent decades. The population dynamics in most of these countries have led to the emergence of a young age structure. High-fertility countries such as Yemen and Afghanistan have the highest proportions of children in the population; while countries like Indonesia and Bangladesh, where fertility is approaching replacement level, have relatively high proportions of youth (aged 15-29) in the population. In Iran, fertility is below replacement level. Education, as an indicator of human capital, has also been improving in all Muslim countries, albeit with considerable variation. These dynamics are creating opportunities and challenges related to the economy, wealth distribution, health, political governance, and socio-economic structures. National development policies should emphasise human development to enable countries to take advantage of these emerging population trends, and to ensure that sustainable development is achieved at all levels. But given the cultural and socio-economic diversity among Islamic countries, context-specific analysis is needed to provide us with a deeper understanding of these population issues, as well as of the pathways to achieving population policy objectives

When studying the economic consequences of changes in the age structure of the population, looking at economic dependency ratios provides us with some descriptive and intuitive initial insights. In this paper, we present two economic dependency ratios. The first ratio is based on economic activity status, and relates the number of dependent individuals to the number of workers. The second dependency ratio relates consumption to total labour income. To build up the second ratio, we rely on the recently set up National Transfer Accounts (NTA) for Austria. Simulations of the employment-based dependency ratio with constant age-specific employment rates indicate that the employment-based dependency ratio will increase from 1.23 in 2010 to 1.88 in 2050, based on a population scenario that assumes low mortality and high educational levels in the future. The corresponding values for the NTA-based dependency with constant age-specific labour income and consumption are 1.12 in 2010 and 1.49 in 2050. We then compare how the dependency ratio would differ if we accounted for the increasing levels of educational attainment. While the education-specific age patterns of economic activities are kept constant as of 2010, the changing educational composition up to 2050 is accounted for. In Austria, higher educated individuals enter and exit the labour market at older ages and have more total labour income than lower educated individuals. Our simulations of the education-specific economic dependency ratios up to 2050, based on the optimistic projection scenario of low mortality and high educational levels in the future, show that the employment-based ratio will increase to 1.68 and the NTA-based dependency ratio will rise to 1.28. These increases are still considerable, but are well below the values found when changes in the educational composition are not taken into account. We can therefore conclude that the trend towards higher levels of educational attainment may help to reduce economic dependency.

In 2016, the Joint Research Centre (JRC) of the European Commission and the International Institute for Applied Systems Analysis (IIASA) agreed to form a partnership, establishing the Centre of Expertise on Population and Migration (CEPAM). The work presented here summarises the first results published by CEPAM. The results reveal clear momentum towards population ageing, and how migration has limited ability to influence the population structure of the EU, especially in the long-run. On the other hand, boosting labour force participation can nullify expected rises in the dependency ratio from population ageing. Globally, the findings show the future of population growth and socio-economic development will be determined by the expansion of education, particularly among girls in Africa. Scenarios of either rapid or stalled development illustrate a large range of possible futures for world population by 2100.

The theory of the “(first) demographic transition” (DT) still has considerable practical relevance in the field of population research. For instance, the DT serves as a conceptual model that underlies the UN’s population projections, and is central to the discussion around the so-called “demographic dividend”. Although it was first described 90 years ago, several questions related to the DT remain open or need verification. In particular, there is debate about the question of what the indispensable triggers of the DT are. Assumptions regarding the primary causes include increased education for women and related changes in values, as well as economic development, urbanisation, migration, and the democratisation process. This paper aims to contribute to DT-related research using an innovative research approach. Our study covers all 102 countries with populations that have undergone the DT between 1950 and 2010. Among these countries, we identified 25 populations that passed through this process at an exceptionally high tempo. We refer to this process as “express transitioning” (ET), and seek to identify its main determinants by comparing the ET populations with the populations of the other DT countries. The data we use are taken from the Wittgenstein Centre Data Explorer, the UN World Population Prospects, the UN World Urbanization Prospects, the World Bank Group, and the Center for Systematic Peace. Our analysis is based on rather descriptive methods, including ANOVA tests and bivariate correlations. We find that the urbanisation level and the education dynamics are most closely associated with ET, whereas other variables show no significant association with the ET process.